Genetic Algorithms for Optimal Reactive Power Compensation of a Power System with Wind Generators based on Artificial Neural Networks

被引:0
|
作者
Krichen, L. [1 ]
Abdallah, H. Hadj [1 ]
Ouali, A. [1 ]
机构
[1] Natl Sch Engn Sfax, BP W, Sfax 3038, Tunisia
关键词
Optimal Reactive Power; Wind Park; Active Losses; Optimization; Genetic Algorithm (GA); Artificial Neural Networks (ANN);
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we develop a method to maintain an acceptable voltages profile and minimization of active losses of a power system including wind generators in real time. These tasks are ensured by acting on capacitor and inductance benches implemented in the consuming nodes. To solve this problem, we minimize an objective function associated to active losses under constraints imposed on the voltages and the reactive productions of the various benches. The minimization procedure was realised by the use of genetic algorithms (GA). The major disadvantage of this technique is that it requires a significant computing time thus not making it possible to deal with the problem in real time. After a training phase, a neural model has the capacity to provide a good estimation of the voltages, the reactive productions and the losses for forecast curves of the load and the wind speed, in real time.
引用
收藏
页码:1 / 12
页数:12
相关论文
共 50 条
  • [1] Genetic algorithms for optimal reactive power compensation on the National Grid system
    Li, F
    Pilgrim, JD
    Dabeedin, C
    Chebbo, A
    Aggarwal, RK
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (01) : 493 - 500
  • [2] Genetic algorithms for optimal reactive power compensation on the national grid system
    Pilgrim, JD
    Li, F
    Aggarwal, RK
    [J]. 2002 IEEE POWER ENGINEERING SOCIETY SUMMER MEETING, VOLS 1-3, CONFERENCE PROCEEDINGS, 2002, : 524 - 529
  • [3] ANN for multi-objective optimal reactive compensation of a power system with wind generators
    Krichen, Lotfi
    Ben Aribia, Houssem
    Abdallah, Hsan Hadj
    Ouali, Abderrazak
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2008, 78 (09) : 1511 - 1519
  • [4] Optimal reactive power planning in distribution system with wind power generators
    Liu, Xue-Ping
    Liu, Tian-Qi
    Li, Xing-Yuan
    [J]. Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2010, 38 (20): : 130 - 135
  • [5] Genetic algorithms for optimal Reactive Power Compensation Planning on the national grid system
    Pilgrim, JD
    Li, FL
    [J]. FIFTH INTERNATIONAL CONFERENCE ON POWER SYSTEM MANAGEMENT AND CONTROL, 2002, (488): : 408 - 413
  • [6] Reactive Power Compensation Based on Artificial Neural Network
    Bayindir, Ramazan
    Sagiroglu, Seref
    Colak, Ilhami
    [J]. JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, 2007, 10 (02): : 129 - 135
  • [7] Optimal Power Flow Using PSO Algorithms Based on Artificial Neural Networks
    Butti, Omar Sagban Taghi Al
    Burunkaya, Mustafa
    Rahebi, Javad
    Lopez-Guede, Jose Manuel
    [J]. IEEE Access, 2024, 12 : 154778 - 154795
  • [8] OPTIMAL REACTIVE POWER DISPATCH BASED ON ARTIFICIAL NEURAL NETWORK IN POWER SYSTEMS
    Liu, Baozhu
    [J]. PROCEEDINGS OF THE 38TH INTERNATIONAL CONFERENCE ON COMPUTERS AND INDUSTRIAL ENGINEERING, VOLS 1-3, 2008, : 2704 - 2709
  • [9] Cataclysmic genetic algorithms based optimal reactive power planning
    Zhang, Yongjun
    Ren, Zhen
    Zhong, Hongmei
    Tang, Zhuoyao
    Shang, Chun
    [J]. Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2002, 26 (23): : 29 - 32
  • [10] Optimal Reactive Power Planning of Doubly Fed Induction Generators Using Genetic Algorithms
    Sangsarawut, P.
    Oonsivilai, A.
    Kulworawanichpong, T.
    [J]. RECENT ADVANCES IN ENERGY AND ENVIRONMENT, 2010, : 278 - +